π Guang-Ze Yang
Researcher in Control Theory & Robotics
Also Known As
Grayson Young
ζ₯ εΊζ²’ (γγ γγγγ)
ζ¨ εΉΏζ³½ (Yang Guang-Ze)
π About Me'
I build optimal, safety-critical controllers for multi-robot systems. At Ibaraki University (Japan), my research focuses on enabling teams of robots to collaborate effectively through distributed and robust optimal control strategies in real-time. Through my blog id: 'about.aboutMe.descriptionContinued', message: '(Japan), my research focuses on enabling teams of robots to collaborate effectively through distributed and robust optimal control strategies in real-time. Through my blog', description: 'About Me description part 2' Notebook, I share knowledge and insights on robotics, control theory, programming, and personal growth.
π― Current Focus
- Research: Model Predictive Control (MPC), Control Barrier Functions (CBF)
- Status: Starting full-time career in autonomous multi-robot systems research, April 2026
- Building: Open-source projects related to MPC, CBF and formation control
- Learning: Publishing for academic journals
π¬ Research Interests
- Optimal & Robust Control
Applying advanced control theory to ensure system performance and stability under disturbances and model uncertainties. - Distributed Multi-Robot Control
Designing decentralized algorithms that enable robot teams to perform complex tasks collaboratively. - Motion Control & Path Planning
Developing algorithms for autonomous robot navigation and obstacle avoidance.
π Education
Master of Engineering
Mechanical Systems Engineering
Ibaraki University
April 2024 β March 2026Bachelor of Engineering
Mechanical Systems Engineering
Ibaraki University
April 2020 β March 2024π Publications
Distributed Robust Time-Varying Formation Control of Multi-Agent Systems Under Disturbances
SICE FES, 2024
This work considers the problem of time-varying formation tracking control of second-order multi-agent systems under disturbances. A distributed robust time-varying formation control law is proposed including distributed finite-time estimators of the leader states and sliding mode time-varying formation controllers.
β‘ Technical Skills Overview
π» Programming & Platforms
Control System Simulation
Data Analysis, AI/ML
Container
Development Environment
π€ Robotics
Robot Operating System
Real-time Systems
Embedded Systems
CAD Design
π₯ Core Knowledge Areas
Optimal & Robust Control, Nonlinear multi-robot Systems
Kinematics, Dynamics, Mobile Robotics.
Convex Optimization, Nonlinear Programming (NLP)
Reinforcement Learning, Neural Networks
π οΈ Tools
Version Control & Collaboration
Academic Publishing
IDE
High-Performance Python Packager
π Languages
Chinese
English
Japanese
π Personal Interests
- Fitness
Training & running 4-5Γ/week - Sports
Weekly basketball sessions - Reading
Biography, Philosophy, Self-improvement
- Gaming
Zelda, Fire Emblem, Monster Hunter - Music
J-pop, R&B, International
π Philosophy
"Stoic in hardship, humble in success."
"η₯δΉθ δΈε¦ε₯½δΉθ οΌε₯½δΉθ δΈε¦ζ¨δΉθ γ" β Confucius
This philosophy forms the cornerstone of my approach to both research and life. I believe that pursuing meaningful work demands the perseverance to face challenging, long-term problems, as well as the humility to continuously learn from new insights and to collaborate openly and effectively with others.
π¬ Let's Connect!
I'm always open to discussing research opportunities, collaboration, or connecting with fellow enthusiasts in robotics and control systems.